Show simple item record

dc.contributor.author
Schotten, Roman
dc.contributor.author
Mühlhofer, Evelyn
dc.contributor.author
Chatzistefanou, Georgios-Alexandros
dc.contributor.author
Bachmann, Daniel
dc.contributor.author
Chen, Albert S.
dc.contributor.author
Koks, Elco E.
dc.date.accessioned
2024-02-19T09:39:32Z
dc.date.available
2024-02-19T06:57:54Z
dc.date.available
2024-02-19T09:39:32Z
dc.date.issued
2024-03-01
dc.identifier.other
10.1016/j.rcns.2024.01.002
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/660134
dc.identifier.doi
10.3929/ethz-b-000660134
dc.description.abstract
Natural hazards impact interdependent infrastructure networks that keep modern society functional. While a variety of modelling approaches are available to represent critical infrastructure networks (CINs) on different scales and analyse the impacts of natural hazards, a recurring challenge for all modelling approaches is the availability and accessibility of sufficiently high-quality input and validation data. The resulting data gaps often require modellers to assume specific technical parameters, functional relationships, and system behaviours. In other cases, expert knowledge from one sector is extrapolated to other sectoral structures or even cross-sectorally applied to fill data gaps. The uncertainties introduced by these assumptions and extrapolations and their influence on the quality of modelling outcomes are often poorly understood and difficult to capture, thereby eroding the reliability of these models to guide resilience enhancements. Additionally, ways of overcoming the data availability challenges in CIN modelling, with respect to each modelling purpose, remain an open question. To address these challenges, a generic modelling workflow is derived from existing modelling approaches to examine model definition and validations, as well as the six CIN modelling stages, including mapping of infrastructure assets, quantification of dependencies, assessment of natural hazard impacts, response & recovery, quantification of CI services, and adaptation measures. The data requirements of each stage were systematically defined, and the literature on potential sources was reviewed to enhance data collection and raise awareness of potential pitfalls. The application of the derived workflow funnels into a framework to assess data availability challenges. This is shown through three case studies, taking into account their different modelling purposes: hazard hotspot assessments, hazard risk management, and sectoral adaptation. Based on the three model purpose types provided, a framework is suggested to explore the implications of data scarcity for certain data types, as well as their reasons and consequences for CIN model reliability. Finally, a discussion on overcoming the challenges of data scarcity is presented.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Critical infrastructure networks
en_US
dc.subject
Impact modelling
en_US
dc.subject
Data availability
en_US
dc.subject
Natural hazards
en_US
dc.title
Data for critical infrastructure network modelling of natural hazard impacts: Needs and influence on model characteristics
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2024-02-12
ethz.journal.title
Resilient Cities and Structures
ethz.journal.volume
3
en_US
ethz.journal.issue
1
en_US
ethz.pages.start
55
en_US
ethz.pages.end
65
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.scopus
ethz.publication.status
published
en_US
ethz.relation.isCitedBy
10.3929/ethz-b-000661301
ethz.date.deposited
2024-02-19T06:57:55Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2024-02-19T09:39:33Z
ethz.rosetta.lastUpdated
2025-02-14T08:03:03Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Data%20for%20critical%20infrastructure%20network%20modelling%20of%20natural%20hazard%20impacts:%20Needs%20and%20influence%20on%20model%20characteristics&rft.jtitle=Resilient%20Cities%20and%20Structures&rft.date=2024-03-01&rft.volume=3&rft.issue=1&rft.spage=55&rft.epage=65&rft.au=Schotten,%20Roman&M%C3%BChlhofer,%20Evelyn&Chatzistefanou,%20Georgios-Alexandros&Bachmann,%20Daniel&Chen,%20Albert%20S.&rft.genre=article&rft_id=info:doi/10.1016/j.rcns.2024.01.002&
 Search print copy at ETH Library

Files in this item

Thumbnail

Publication type

Show simple item record